Exploring Remote Power Attacks Targeting Parallel Data Encryption On Multi-Tenant FPGAs
Yankun Zhu, Jindong Zhou, Pingqiang Zhou · 2023
Cloud service providers (CSPs) are increasingly incorporating Field Programmable Gate Arrays (FPGAs) into their cloud data centers due to the benefits of their flexibility and high performance in heterogeneous designs. However, the optimization of hardware resource utilization through multi-tenancy presents new security concerns. Prior research has demonstrated that remote side-channel attacks represent a significant security threat in the case of a single Advanced Encryption Standard (AES) module. However, it remains an open question whether parallel encryption can offer natural protection against Correlation Power Analysis (CPA). Our research focuses on side-channel attacks on parallel data encryption modules. We implemented delay-line based power sensors to collect mixed power traces and conducted CPA to steal the cipher key. Our results show that clocking methodology would have a significant influence on data protection. If parallel modules work at the same frequency without difference in clocking phase, the mixed voltage drops would contain sufficient information for attackers to decrypt the cipher key. Nevertheless, once the victim applies unique clocking phase to each module, he would convert voltage fluctuations from other modules into noises that offer a natural protection mechanism for parallel data encryption.